Some embodiments of the present disclosure are directed to an approach for implementing normalized ranking of semantic query search results.
Ranking of query results using lexical ranking often employs techniques to count the number of occurrences of a particular lexical term (e.g., a search term, an indexed search term, etc.) and ranks a plurality of matching documents based on the occurrence count. In contrast, semantic searching for matching documents places more emphasis on the meaning within the documents. Thus, merely ranking a plurality of matching documents based on the occurrence count is deficient for ranking the relevance of documents returned from a semantic query.
Given the aforementioned deficiencies of such lexical ranking techniques, and further deficiencies in applying such lexical ranking techniques to rank results of semantic queries, consideration of these deficiencies in the context of retrieval of documents based on unstructured data gives rise to the need for semantic indexing and ranking based on semantic constructions that relate a subject, a property, and an object into a “triple”. Such use of triples in indexing and retrieving documents based on semantic queries is an area of focus for standardization organizations such as W3C, however legacy techniques for ranking need to be improved upon when ranking search results from a semantic query.
Therefore, there is a need for an improved approach.